Abstract: A comparative analysis is conducted to evaluate the performance of several classical priority rules for the resource-constrained project scheduling problem with flexible network structures, stochastic activity durations, and random rework. Flexible project scheduling involves two interrelated subproblems, namely activity selection and activity sequencing, which may be addressed using either identical or different priority rules. To more accurately capture the impact of random rework on activity prioritization, a priority evaluation method based on aggregated remaining processing time estimation is proposed. A comprehensive set of test instances covering diverse problem characteristics is constructed, and extensive simulation experiments are conducted to compare the performance of single priority rules and paired priority rules under different scheduling environments. Results show that paired rules significantly outperform single rules, and the best-performing rules differ from those reported in the literature for deterministic problem settings. In addition, project flexibility and resource tightness are found to have significant influence on the performance of priority rules, whereas the effects of other factors are relatively limited. Overall, the TTSL–MSLK paired rule performs best when resources are relatively abundant, while the TTSL–LFT paired rule exhibits superior performance in other settings. These findings provide valuable insights for selecting appropriate scheduling rules in practical engineering applications.